Inter-layer and inter-subject variability of circadian gene expression in human skin
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PROVIDER: PRJNA844020 | ENA |
REPOSITORIES: ENA
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Project description:This work reports 24 h gene expression rhythms in two skin layers, epidermis and dermis, in a cohort of young, healthy adults, who maintained natural, regular sleep-wake schedules. 10% of the expressed genes showed such diurnal rhythms at the population level, of which only a third differed between the two layers. Amplitude and phases of diurnal gene expression varied more across subjects than layers, with amplitude being more variable than phases. Expression amplitudes in the epidermis were larger and more subject-variable, while they were smaller and more consistent in the dermis. Core clock gene expression was similar across layers at the population-level, but were heterogeneous in their variability across subjects. This work provides a valuable resource to advance our understanding of human skin and presents a novel methodology to quantify sources of variability in human circadian rhythms.
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Project description:The skin is the largest human organ with a circadian clock that regulates its function. Although circadian rhythms in specific functions are known, rhythms in the proximal clock output, gene expression, in human skin have not been thoroughly explored. This work reports 24 h gene expression rhythms in two skin layers, epidermis and dermis, in a cohort of young, healthy adults, who maintained natural, regular sleep-wake schedules. 10% of the expressed genes showed such diurnal rhythms at the population level, of which only a third differed between the two layers. Amplitude and phases of diurnal gene expression varied more across subjects than layers, with amplitude being more variable than phases. Expression amplitudes in the epidermis were larger and more subject-variable, while they were smaller and more consistent in the dermis. Core clock gene expression was similar across layers at the population-level, but were heterogeneous in their variability across subjects. We also identified small sets of biomarkers for internal clock phase in each layer, which consisted of layer-specific non-core clock genes. This work provides a valuable resource to advance our understanding of human skin and presents a novel methodology to quantify sources of variability in human circadian rhythms.
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Project description:A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered and could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform and has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability over a 24 hours time-course between individual Arabidopsis thaliana plants growing in stable conditions. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses. We also identified factors that might facilitate gene expression variability, such as gene size, the number of transcription factors regulating a gene and the chromatin environment. These results will bring a new light into the impact of transcriptional variability in gene expression regulation in plants.
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Project description:Pathological consequences of circadian misalignment, such as shift work, show considerable individual differences, but the lack of mechanistic understanding hinders precision prevention to prevent and mitigate disease symptoms. Here, we employed an integrative approach involving physiological, transcriptional, and histological phenotypes to examine inter-individual differences in pathological progression during the pre-symptomatic stage, prior to the development of irreversible diseases under chronic circadian misalignment, using wild-type mice exposed to chronic jet-lag (CJL). We observed that CJL markedly increased the prevalence of hepatic steatosis with pronounced inter-individual differences. Stratification of individual mice based on CJL-induced hepatic transcriptomic signature, validated by histopathological analysis, pinpoints dysregulation of lipid metabolism. Moreover, the period and power of intrinsic behavioral rhythms was found to significantly correlate with CJL-induced gene signatures. Together, our results suggest circadian rhythm robustness of the animals contribute to inter-individual variations in pathogenesis of circadian misalignment-induced diseases, and arise the possibility that these physiological indicators may be available for predictive hallmarks of circadian rhythm disorders.
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Project description:The stop signal task has been used to quantify the human inhibitory control. The inter-subject and intra-subject variability was investigated under the inhibition of human response with a realistic environmental scenario. In present study, we used a battleground scenario where a sniper-scope picture was the background, a target picture was a go signal, and a nontarget picture was a stop signal. The task instructions were to respond on the target image and inhibit the response if a nontarget image appeared. This scenario produced a threatening situation and endorsed the evaluation of how subject's response inhibition manifests in a real situation. In this study, 32 channels of electroencephalography (EEG) signals were collected from 20 participants during successful stop (response inhibition) and failed stop (response) trials. These EEG signals were used to predict two possible outcomes: successful stop or failed stop. The inter-subject variability (between-subjects) and intra-subject variability (within-subjects) affect the performance of participants in the classification system. The EEG signals of successful stop versus failed stop trials were classified using quadratic discriminant analysis (QDA) and linear discriminant analysis (LDA) (i.e., parametric) and K-nearest neighbor classifier (KNNC) and Parzen density-based (PARZEN) (i.e., nonparametric) under inter- and intra-subject variability. The EEG activities were found to increase during response inhibition in the frontal cortex (F3 and F4), presupplementary motor area (C3 and C4), parietal lobe (P3 and P4), and occipital (O1 and O2) lobe. Therefore, power spectral density (PSD) of EEG signals (1-50Hz) in F3, F4, C3, C4, P3, P4, O1, and O2 electrodes were measured in successful stop and failed stop trials. The PSD of the EEG signals was used as the feature input for the classifiers. Our proposed method shows an intra-subject classification accuracy of 97.61% for subject 15 with QDA classifier in C3 (left motor cortex) and an overall inter-subject classification accuracy of 71.66% ± 9.81% with the KNNC classifier in F3 (left frontal lobe). These results display how inter-subject and intra-subject variability affects the performance of the classification system. These findings can be used effectively to improve the psychopathology of attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), schizophrenia, and suicidality.
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